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In this paper we propose a machine learning approach to classify melanocytic lesions as malignant or benign, using dermoscopic images. The lesion features used in the classification framework are inspired on border, texture, color and structures used in popular dermoscopy algorithms performed by clinicians by visual inspection. The main weakness of(More)
Shape recognition is the field of computer vision which addresses the problem of finding out whether a query shape lies or not in a shape database, up to a certain invariance. Most shape recognition methods simply sort shapes from the database along some (dis-)similarity measure to the query shape. Their main weakness is the decision stage, which should aim(More)
Shape recognition systems usually order a fixed number of best matches to each query, but do not address or answer the two following questions: Is a query shape in a given database ? How can we be sure that a match is correct ? This communication deals with these two key points. A database being given, with each shape S and each distance δ, we associate its(More)
A unified a contrario detection method is proposed to solve three classical problems in clustering analysis. The first one is to evaluate the validity of a cluster candidate. The second problem is that meaningful clusters can contain or be contained in other meaningful clusters. A rule is needed to define locally optimal clusters by inclusion. The third(More)
—We describe a method that allows for accurate in-flight calibration of the interior orientation of any pushbroom camera and that in particular solves the problem of modeling the distortions induced by charge coupled device (CCD) misalign-ments. The distortion induced on the ground by each CCD is measured using subpixel correlation between the(More)
This article proposes a new multiscale filter accelerating Monte Carlo renderer. Each pixel in the image is characterized by the colors of the rays that reach its surface. The proposed filter uses a statistical distance to compare with each other the ray color distributions associated with different pixels, at each scale. Based on this distance, it decides(More)
Computer Tomographic Colonography, combined with computer-aided detection (CAD), is a promising emerging technique for colonic polyp analysis. We present a CAD scheme for polyp flagging based on new texture and geometric features that consider both the information in the candidate polyp location and its immediate surrounding area, testing multiple sizes.(More)
Normalized Cuts is a state-of-the-art spectral method for clustering. By applying spectral techniques, the data becomes easier to cluster and then k-means is classically used. Unfortunately the number of clusters must be manually set and it is very sensitive to initialization. Moreover, k-means tends to split large clusters, to merge small clusters, and to(More)
In refractory epilepsy, the goal of neuroimaging is to localize the region of seizure onset. Tracers that accumulate and remain fixed proportional to regional cerebral blood flow (rCBF) at the time of injection are used to obtain SPECT images of the brain activity during and between seizures. The most used technique for detecting the epileptogenic zone (EZ)(More)